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Head of Data & AI
StarComplianceHead of Data & AI at StarCompliance, leading AI strategy and product capability development in cloud-native SaaS environment. Collaborating with Product, Engineering, and Executive teams.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI and ML system delivery, focusing on generative AI, LLM-based architectures, and data engineering. Proven ability to lead high-performing teams and align AI initiatives with business strategy in regulated domains.
Highest-signal resume keywords
Generative AI ArchitectureMLOps CapabilitiesData EngineeringAzure Ecosystem ExperienceProduction-Grade AI Systems
ATS Keywords
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Hard Skills
Generative AILLM-Based ApplicationsData Pipeline ArchitectureModel Training PipelinesVersioningMonitoringA/B ExperimentationDrift DetectionData ModelingELT/ETL Patterns
Soft Skills
LeadershipMentoringCommercial Instincts
Tools & Technologies
SnowflakeAzure Data FactoryAzure SynapseAzure OpenAI ServiceAzure Machine LearningPineconeWeaviatePgvectorAzure AI Search
Industry Keywords
Financial ServicesRegtechComplianceSurveillance
Tech Stack
Tools & technologiesAzureCloudETLMicroservices
About the role
Key responsibilities & impact- Own the end-to-end technical strategy and execution roadmap for AI-enabled product capabilities across the StarCompliance platform.
- Drive adoption of generative AI, LLM-based architectures, predictive analytics, graph intelligence, recommendation systems, and semantic search where these deliver measurable customer value.
- Own the data foundation strategy, ensuring clean, trusted, well-governed data underpins every AI initiative.
- Build robust MLOps capabilities, including model training pipelines, versioning, monitoring, A/B experimentation, and drift detection.
- Champion pragmatic AI adoption within engineering and product development, accelerating how we build, not just what we build.
- Build, mentor, and scale a high-performing Data & AI organisation across data engineering, data science, ML engineering and analytics.
- Work closely with the CTO and executive team to align AI and data initiatives with company strategy and commercial priorities.
- Partner with the Product Director, AI & Data Products, co-owning the AI roadmap, prioritisation, and delivery outcomes.
Requirements
What you’ll need- Proven delivery of production-grade AI and ML systems at scale, not just experimentation.
- Deep experience with generative AI and LLM-based applications architectures (fine-tuning, prompt engineering, RAG, agentic frameworks).
- Strong knowledge of vector databases and semantic search (e.g. Pinecone, Weaviate, pgvector, Azure AI Search).
- Deep background in modern data engineering, ELT/ETL patterns, and large-scale data pipeline architectures.
- Hands-on experience with Snowflake (or equivalent cloud data warehouse) and associated data modeling patterns.
- Strong Azure ecosystem experience: Azure Data Factory, Azure Synapse, Azure OpenAI Service, and Azure Machine Learning.
- Strong software engineering fundamentals and the credibility to engage at technical depth with senior engineers.
- Experience with cloud-native, microservices, and event-driven architectures on Azure (or equivalent hyperscaler).
- Ability to make sound build vs buy vs integrate decisions across the AI and data tooling landscape.
- Proven experience building and leading high-performing Data / AI engineering teams.
- Experience within financial services, regtech, compliance, surveillance, or similarly regulated domains.
- Strong commercial instincts — the ability to connect technical investment to customer value and business outcomes.
Benefits
Comp & perks- All StarCompliance employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner.